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Author (down) Jose Manuel Alvarez; Theo Gevers; Antonio Lopez edit  url
doi  openurl
  Title Evaluating Color Representation for Online Road Detection Type Conference Article
  Year 2013 Publication ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars Abbreviated Journal  
  Volume Issue Pages 594-595  
  Keywords  
  Abstract Detecting traversable road areas ahead a moving vehicle is a key process for modern autonomous driving systems. Most existing algorithms use color to classify pixels as road or background. These algorithms reduce the effect of lighting variations and weather conditions by exploiting the discriminant/invariant properties of different color representations. However, up to date, no comparison between these representations have been conducted. Therefore, in this paper, we perform an evaluation of existing color representations for road detection. More specifically, we focus on color planes derived from RGB data and their most com-
mon combinations. The evaluation is done on a set of 7000 road images acquired
using an on-board camera in different real-driving situations.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CVVT:E2M  
  Notes ADAS;ISE Approved no  
  Call Number Admin @ si @ AGL2013 Serial 2794  
Permanent link to this record
 

 
Author (down) Jorge Bernal; F. Javier Sanchez; Fernando Vilariño edit   pdf
doi  openurl
  Title Impact of Image Preprocessing Methods on Polyp Localization in Colonoscopy Frames Type Conference Article
  Year 2013 Publication 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Abbreviated Journal  
  Volume Issue Pages 7350 - 7354  
  Keywords  
  Abstract In this paper we present our image preprocessing methods as a key part of our automatic polyp localization scheme. These methods are used to assess the impact of different endoluminal scene elements when characterizing polyps. More precisely we tackle the influence of specular highlights, blood vessels and black mask surrounding the scene. Experimental results prove that the appropriate handling of these elements leads to a great improvement in polyp localization results.  
  Address Osaka; Japan; July 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1557-170X ISBN Medium  
  Area 800 Expedition Conference EMBC  
  Notes MV; 600.047; 600.060;SIAI Approved no  
  Call Number Admin @ si @ BSV2013 Serial 2286  
Permanent link to this record
 

 
Author (down) Jorge Bernal; David Vazquez (eds) edit   pdf
isbn  openurl
  Title Computer vision Trends and Challenges Type Book Whole
  Year 2013 Publication Computer vision Trends and Challenges Abbreviated Journal  
  Volume Issue Pages  
  Keywords CVCRD; Computer Vision  
  Abstract This book contains the papers presented at the Eighth CVC Workshop on Computer Vision Trends and Challenges (CVCR&D'2013). The workshop was held at the Computer Vision Center (Universitat Autònoma de Barcelona), the October 25th, 2013. The CVC workshops provide an excellent opportunity for young researchers and project engineers to share new ideas and knowledge about the progress of their work, and also, to discuss about challenges and future perspectives. In addition, the workshop is the welcome event for new people that recently have joined the institute.

The program of CVCR&D is organized in a single-track single-day workshop. It comprises several sessions dedicated to specific topics. For each session, a doctor working on the topic introduces the general research lines. The PhD students expose their specific research. A poster session will be held for open questions. Session topics cover the current research lines and development projects of the CVC: Medical Imaging, Medical Imaging, Color & Texture Analysis, Object Recognition, Image Sequence Evaluation, Advanced Driver Assistance Systems, Machine Vision, Document Analysis, Pattern Recognition and Applications. We want to thank all paper authors and Program Committee members. Their contribution shows that the CVC has a dynamic, active, and promising scientific community.

We hope you all enjoy this Eighth workshop and we are looking forward to meeting you and new people next year in the Ninth CVCR&D.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor Jorge Bernal; David Vazquez  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-84-940902-2-6 Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number ADAS @ adas @ BeV2013 Serial 2339  
Permanent link to this record
 

 
Author (down) Jordi Roca; C. Alejandro Parraga; Maria Vanrell edit   pdf
doi  openurl
  Title Chromatic settings and the structural color constancy index Type Journal Article
  Year 2013 Publication Journal of Vision Abbreviated Journal JV  
  Volume 13 Issue 4-3 Pages 1-26  
  Keywords  
  Abstract Color constancy is usually measured by achromatic setting, asymmetric matching, or color naming paradigms, whose results are interpreted in terms of indexes and models that arguably do not capture the full complexity of the phenomenon. Here we propose a new paradigm, chromatic setting, which allows a more comprehensive characterization of color constancy through the measurement of multiple points in color space under immersive adaptation. We demonstrated its feasibility by assessing the consistency of subjects' responses over time. The paradigm was applied to two-dimensional (2-D) Mondrian stimuli under three different illuminants, and the results were used to fit a set of linear color constancy models. The use of multiple colors improved the precision of more complex linear models compared to the popular diagonal model computed from gray. Our results show that a diagonal plus translation matrix that models mechanisms other than cone gain might be best suited to explain the phenomenon. Additionally, we calculated a number of color constancy indices for several points in color space, and our results suggest that interrelations among colors are not as uniform as previously believed. To account for this variability, we developed a new structural color constancy index that takes into account the magnitude and orientation of the chromatic shift in addition to the interrelations among colors and memory effects.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes CIC; 600.052; 600.051; 605.203 Approved no  
  Call Number Admin @ si @ RPV2013 Serial 2288  
Permanent link to this record
 

 
Author (down) Joost Van de Weijer; Fahad Shahbaz Khan; Marc Masana edit   pdf
doi  isbn
openurl 
  Title Interactive Visual and Semantic Image Retrieval Type Book Chapter
  Year 2013 Publication Multimodal Interaction in Image and Video Applications Abbreviated Journal  
  Volume 48 Issue Pages 31-35  
  Keywords  
  Abstract One direct consequence of recent advances in digital visual data generation and the direct availability of this information through the World-Wide Web, is a urgent demand for efficient image retrieval systems. The objective of image retrieval is to allow users to efficiently browse through this abundance of images. Due to the non-expert nature of the majority of the internet users, such systems should be user friendly, and therefore avoid complex user interfaces. In this chapter we investigate how high-level information provided by recently developed object recognition techniques can improve interactive image retrieval. Wel apply a bagof- word based image representation method to automatically classify images in a number of categories. These additional labels are then applied to improve the image retrieval system. Next to these high-level semantic labels, we also apply a low-level image description to describe the composition and color scheme of the scene. Both descriptions are incorporated in a user feedback image retrieval setting. The main objective is to show that automatic labeling of images with semantic labels can improve image retrieval results.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Angel Sappa; Jordi Vitria  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1868-4394 ISBN 978-3-642-35931-6 Medium  
  Area Expedition Conference  
  Notes CIC; 605.203; 600.048 Approved no  
  Call Number Admin @ si @ WKC2013 Serial 2284  
Permanent link to this record
 

 
Author (down) Joost Van de Weijer; Fahad Shahbaz Khan edit   pdf
doi  isbn
openurl 
  Title Fusing Color and Shape for Bag-of-Words Based Object Recognition Type Conference Article
  Year 2013 Publication 4th Computational Color Imaging Workshop Abbreviated Journal  
  Volume 7786 Issue Pages 25-34  
  Keywords Object Recognition; color features; bag-of-words; image classification  
  Abstract In this article we provide an analysis of existing methods for the incorporation of color in bag-of-words based image representations. We propose a list of desired properties on which bases fusing methods can be compared. We discuss existing methods and indicate shortcomings of the two well-known fusing methods, namely early and late fusion. Several recent works have addressed these shortcomings by exploiting top-down information in the bag-of-words pipeline: color attention which is motivated from human vision, and Portmanteau vocabularies which are based on information theoretic compression of product vocabularies. We point out several remaining challenges in cue fusion and provide directions for future research.  
  Address Chiba; Japan; March 2013  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-36699-4 Medium  
  Area Expedition Conference CCIW  
  Notes CIC; 600.048 Approved no  
  Call Number Admin @ si @ WeK2013 Serial 2283  
Permanent link to this record
 

 
Author (down) Jon Almazan; Alicia Fornes; Ernest Valveny edit   pdf
doi  openurl
  Title A Deformable HOG-based Shape Descriptor Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1022-1026  
  Keywords  
  Abstract In this paper we deal with the problem of recognizing handwritten shapes. We present a new deformable feature extraction method that adapts to the shape to be described, dealing in this way with the variability introduced in the handwriting domain. It consists in a selection of the regions that best define the shape to be described, followed by the computation of histograms of oriented gradients-based features over these points. Our results significantly outperform other descriptors in the literature for the task of hand-drawn shape recognition and handwritten word retrieval  
  Address Washington; USA; August 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1520-5363 ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number Admin @ si @ AFV2013 Serial 2326  
Permanent link to this record
 

 
Author (down) Jon Almazan; Albert Gordo; Alicia Fornes; Ernest Valveny edit   pdf
doi  openurl
  Title Handwritten Word Spotting with Corrected Attributes Type Conference Article
  Year 2013 Publication 15th IEEE International Conference on Computer Vision Abbreviated Journal  
  Volume Issue Pages 1017-1024  
  Keywords  
  Abstract We propose an approach to multi-writer word spotting, where the goal is to find a query word in a dataset comprised of document images. We propose an attributes-based approach that leads to a low-dimensional, fixed-length representation of the word images that is fast to compute and, especially, fast to compare. This approach naturally leads to an unified representation of word images and strings, which seamlessly allows one to indistinctly perform query-by-example, where the query is an image, and query-by-string, where the query is a string. We also propose a calibration scheme to correct the attributes scores based on Canonical Correlation Analysis that greatly improves the results on a challenging dataset. We test our approach on two public datasets showing state-of-the-art results.  
  Address Sydney; Australia; December 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1550-5499 ISBN Medium  
  Area Expedition Conference ICCV  
  Notes DAG Approved no  
  Call Number Admin @ si @ AGF2013 Serial 2327  
Permanent link to this record
 

 
Author (down) Joan Serrat; Felipe Lumbreras; Antonio Lopez edit   pdf
doi  openurl
  Title Cost estimation of custom hoses from STL files and CAD drawings Type Journal Article
  Year 2013 Publication Computers in Industry Abbreviated Journal COMPUTIND  
  Volume 64 Issue 3 Pages 299-309  
  Keywords On-line quotation; STL format; Regression; Gaussian process  
  Abstract We present a method for the cost estimation of custom hoses from CAD models. They can come in two formats, which are easy to generate: a STL file or the image of a CAD drawing showing several orthogonal projections. The challenges in either cases are, first, to obtain from them a high level 3D description of the shape, and second, to learn a regression function for the prediction of the manufacturing time, based on geometric features of the reconstructed shape. The chosen description is the 3D line along the medial axis of the tube and the diameter of the circular sections along it. In order to extract it from STL files, we have adapted RANSAC, a robust parametric fitting algorithm. As for CAD drawing images, we propose a new technique for 3D reconstruction from data entered on any number of orthogonal projections. The regression function is a Gaussian process, which does not constrain the function to adopt any specific form and is governed by just two parameters. We assess the accuracy of the manufacturing time estimation by k-fold cross validation on 171 STL file models for which the time is provided by an expert. The results show the feasibility of the method, whereby the relative error for 80% of the testing samples is below 15%.  
  Address  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS; 600.057; 600.054; 605.203 Approved no  
  Call Number Admin @ si @ SLL2013; ADAS @ adas @ Serial 2161  
Permanent link to this record
 

 
Author (down) Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño edit   pdf
doi  openurl
  Title Blood Vessel Characterization in Colonoscopy Images to Improve Polyp Localization Type Conference Article
  Year 2013 Publication Proceedings of the International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume 1 Issue Pages 162-171  
  Keywords Colonoscopy; Blood vessel; Linear features; Valley detection  
  Abstract This paper presents an approach to mitigate the contribution of blood vessels to the energy image used at different tasks of automatic colonoscopy image analysis. This goal is achieved by introducing a characterization of endoluminal scene objects which allows us to differentiate between the trace of 2-dimensional visual objects,such as vessels, and shades from 3-dimensional visual objects, such as folds. The proposed characterization is based on the influence that the object shape has in the resulting visual feature, and it leads to the development of a blood vessel attenuation algorithm. A database consisting of manually labelled masks was built in order to test the performance of our method, which shows an encouraging success in blood vessel mitigation while keeping other structures intact. Moreover, by extending our method to the only available polyp localization
algorithm tested on a public database, blood vessel mitigation proved to have a positive influence on the overall performance.
 
  Address Barcelona; February 2013  
  Corporate Author Thesis  
  Publisher SciTePress Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area 800 Expedition Conference VISIGRAPP  
  Notes MV; 600.054; 600.057;SIAI Approved no  
  Call Number IAM @ iam @ NBS2013 Serial 2198  
Permanent link to this record
 

 
Author (down) Joan M. Nuñez; Debora Gil; Fernando Vilariño edit  doi
openurl 
  Title Finger joint characterization from X-ray images for rheymatoid arthritis assessment Type Conference Article
  Year 2013 Publication 6th International Conference on Biomedical Electronics and Devices Abbreviated Journal  
  Volume Issue Pages 288-292  
  Keywords Rheumatoid Arthritis; X-Ray; Hand Joint; Sclerosis; Sharp Van der Heijde  
  Abstract In this study we propose amodular systemfor automatic rheumatoid arthritis assessment which provides a joint space width measure. A hand joint model is proposed based on the accurate analysis of a X-ray finger joint image sample set. This model shows that the sclerosis and the lower bone are the main necessary features in order to perform a proper finger joint characterization. We propose sclerosis and lower bone detection methods as well as the experimental setup necessary for its performance assessment. Our characterization is used to propose and compute a joint space width score which is shown to be related to the different degrees of arthritis. This assertion is verified by comparing our proposed score with Sharp Van der Heijde score, confirming that the lower our score is the more advanced is the patient affection.  
  Address Barcelona; February 2013  
  Corporate Author Thesis  
  Publisher SciTePress Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area 800 Expedition Conference BIODEVICES  
  Notes IAM;MV; 600.057; 600.054;SIAI Approved no  
  Call Number IAM @ iam @ NGV2013 Serial 2196  
Permanent link to this record
 

 
Author (down) Jiaolong Xu; Sebastian Ramos; Xu Hu; David Vazquez; Antonio Lopez edit   pdf
openurl 
  Title Multi-task Bilinear Classifiers for Visual Domain Adaptation Type Conference Article
  Year 2013 Publication Advances in Neural Information Processing Systems Workshop Abbreviated Journal  
  Volume Issue Pages  
  Keywords Domain Adaptation; Pedestrian Detection; ADAS  
  Abstract We propose a method that aims to lessen the significant accuracy degradation
that a discriminative classifier can suffer when it is trained in a specific domain (source domain) and applied in a different one (target domain). The principal reason for this degradation is the discrepancies in the distribution of the features that feed the classifier in different domains. Therefore, we propose a domain adaptation method that maps the features from the different domains into a common subspace and learns a discriminative domain-invariant classifier within it. Our algorithm combines bilinear classifiers and multi-task learning for domain adaptation.
The bilinear classifier encodes the feature transformation and classification
parameters by a matrix decomposition. In this way, specific feature transformations for multiple domains and a shared classifier are jointly learned in a multi-task learning framework. Focusing on domain adaptation for visual object detection, we apply this method to the state-of-the-art deformable part-based model for cross domain pedestrian detection. Experimental results show that our method significantly avoids the domain drift and improves the accuracy when compared to several baselines.
 
  Address Lake Tahoe; Nevada; USA; December 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference NIPSW  
  Notes ADAS; 600.054; 600.057; 601.217;ISE Approved no  
  Call Number ADAS @ adas @ XRH2013 Serial 2340  
Permanent link to this record
 

 
Author (down) Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez edit  openurl
  Title DA-DPM Pedestrian Detection Type Conference Article
  Year 2013 Publication ICCV Workshop on Reconstruction meets Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords Domain Adaptation; Pedestrian Detection  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICCVW-RR  
  Notes ADAS Approved no  
  Call Number Admin @ si @ XRV2013 Serial 2569  
Permanent link to this record
 

 
Author (down) Jiaolong Xu; David Vazquez; Sebastian Ramos; Antonio Lopez; Daniel Ponsa edit   pdf
doi  openurl
  Title Adapting a Pedestrian Detector by Boosting LDA Exemplar Classifiers Type Conference Article
  Year 2013 Publication CVPR Workshop on Ground Truth – What is a good dataset? Abbreviated Journal  
  Volume Issue Pages 688 - 693  
  Keywords Pedestrian Detection; Domain Adaptation  
  Abstract Training vision-based pedestrian detectors using synthetic datasets (virtual world) is a useful technique to collect automatically the training examples with their pixel-wise ground truth. However, as it is often the case, these detectors must operate in real-world images, experiencing a significant drop of their performance. In fact, this effect also occurs among different real-world datasets, i.e. detectors' accuracy drops when the training data (source domain) and the application scenario (target domain) have inherent differences. Therefore, in order to avoid this problem, it is required to adapt the detector trained with synthetic data to operate in the real-world scenario. In this paper, we propose a domain adaptation approach based on boosting LDA exemplar classifiers from both virtual and real worlds. We evaluate our proposal on multiple real-world pedestrian detection datasets. The results show that our method can efficiently adapt the exemplar classifiers from virtual to real world, avoiding drops in average precision over the 15%.  
  Address Portland; oregon; June 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CVPRW  
  Notes ADAS; 600.054; 600.057; 601.217 Approved yes  
  Call Number XVR2013; ADAS @ adas @ xvr2013a Serial 2220  
Permanent link to this record
 

 
Author (down) Jiaolong Xu; David Vazquez; Antonio Lopez; Javier Marin; Daniel Ponsa edit   pdf
doi  isbn
openurl 
  Title Learning a Multiview Part-based Model in Virtual World for Pedestrian Detection Type Conference Article
  Year 2013 Publication IEEE Intelligent Vehicles Symposium Abbreviated Journal  
  Volume Issue Pages 467 - 472  
  Keywords Pedestrian Detection; Virtual World; Part based  
  Abstract State-of-the-art deformable part-based models based on latent SVM have shown excellent results on human detection. In this paper, we propose to train a multiview deformable part-based model with automatically generated part examples from virtual-world data. The method is efficient as: (i) the part detectors are trained with precisely extracted virtual examples, thus no latent learning is needed, (ii) the multiview pedestrian detector enhances the performance of the pedestrian root model, (iii) a top-down approach is used for part detection which reduces the searching space. We evaluate our model on Daimler and Karlsruhe Pedestrian Benchmarks with publicly available Caltech pedestrian detection evaluation framework and the result outperforms the state-of-the-art latent SVM V4.0, on both average miss rate and speed (our detector is ten times faster).  
  Address Gold Coast; Australia; June 2013  
  Corporate Author Thesis  
  Publisher IEEE Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1931-0587 ISBN 978-1-4673-2754-1 Medium  
  Area Expedition Conference IV  
  Notes ADAS; 600.054; 600.057 Approved no  
  Call Number XVL2013; ADAS @ adas @ xvl2013a Serial 2214  
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